This document details webGL visualisations; webGL is ideal when you have large datasets to plot.
data("montereybay", package = "rayshader") bay <- as.data.frame(as.table(montereybay)) bay$Var1 <- as.numeric(bay$Var1) bay$Var2 <- as.numeric(bay$Var2) bay %>% e_charts(Var1) %>% e_surface(Var2, Freq) %>% e_visual_map(Freq)
quakes %>% e_charts(long) %>% e_geo( roam = TRUE, boundingCoords = list( c(185, - 10), c(165, -40) ) ) %>% e_scatter_gl(lat, depth) %>% e_visual_map()
#Use graphGL for larger networks nodes <- data.frame( name = paste0(LETTERS, 1:300), value = rnorm(300, 10, 2), size = rnorm(300, 10, 2), grp = rep(c("grp1", "grp2", "grp3"), 100), stringsAsFactors = FALSE ) edges <- data.frame( source = sample(nodes$name, 400, replace = TRUE), target = sample(nodes$name, 400, replace = TRUE), stringsAsFactors = FALSE ) e_charts() %>% e_graph_gl() %>% e_graph_nodes(nodes, name, value, size, grp) %>% e_graph_edges(edges, source, target)
Van der Pol oscillator by David Granjon.
vectors <- expand.grid(x = -3:3, y = -3:3) mu <- 1 vectors$sx <- vectors$y vectors$sy <- mu * (1 - vectors$x^2) * vectors$y - vectors$x vectors$color <- log10(runif(nrow(vectors), 1, 10)) vectors %>% e_charts(x) %>% e_flow_gl(y, sx, sy, color) %>% e_visual_map( min = 0, max = 1, # log 10 dimension = 4, # x = 0, y = 1, sx = 3, sy = 4 show = FALSE, # hide inRange = list( color = c('#313695', '#4575b4', '#74add1', '#abd9e9', '#e0f3f8', '#ffffbf', '#fee090', '#fdae61', '#f46d43', '#d73027', '#a50026') ) ) %>% e_x_axis( splitLine = list(show = FALSE) ) %>% e_y_axis( splitLine = list(show = FALSE) )
You can also plot it against different coordinates (coord_system).
latlong <- seq(-180, 180, by = 5) wind = expand.grid(lng = latlong, lat = latlong) wind$slng <- rnorm(nrow(wind), 0, 200) wind$slat <- rnorm(nrow(wind), 0, 200) wind$color <- abs(wind$slat) - abs(wind$slng) trans <- list(opacity = 0.5) # transparency wind %>% e_charts(lng, backgroundColor = '#333') %>% e_geo( itemStyle = list( normal = list( areaColor = "#323c48", borderColor = "#111" ) ) ) %>% e_flow_gl(lat, slng, slat, color, coord_system = "geo", itemStyle = trans, particleSize = 2 ) %>% e_visual_map( color, # range dimension = 4, # lng = 0, lat = 1, slng = 2, slat = 3, color = 4 show = FALSE, # hide inRange = list( color = c('#313695', '#4575b4', '#74add1', '#abd9e9', '#e0f3f8', '#ffffbf', '#fee090', '#fdae61', '#f46d43', '#d73027', '#a50026') ) )